title: Predicting reproductive age with biomarkers of ovarian reserve--how (and what) are we measuring?
abstract: Predicting the reproductive lifespan of an individual woman remains an elusive, yet clinically important, goal. The development of models and staging systems that accurately determine the end of natural fertility and the anticipated age of menopause will represent a significant advance in our ability to counsel women regarding family planning issues and in the individualization of risk assessment. Recent histological and longitudinal investigations have demonstrated a significant relationship between commonly used clinical markers of ovarian reserve and the true ovarian reserve, as assessed by the ovarian nongrowing follicle count and the age of menopause, respectively. Models and staging systems that have been developed based on these findings represent important advances in the field of women's health and promise to provide additional insights into the process of reproductive aging in general. Although the models developed to date appear to improve the prediction of the age of menopause as compared with chronological age alone, wide confidence intervals in the predicted age of menopause and less accurate predictions at ages remote from menopause limit their clinical utility for the individual woman. Future longitudinal and histological investigations are necessary to improve the accuracy of models of reproductive aging.
authors.affiliation: Section of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma.
authors.forename: Karl R
authors.initials: KR
authors.lastname: Hansen
mesh_terms: D000375:Aging; D000818:Animals; D015415:Biomarkers / Q000378:metabolism; D019317:Evidence-Based Medicine; D005260:Female; D006801:Humans; D008954:Models, Biological; D010053:Ovary / Q000254:growth & development / Q000502:physiology / Q000503:physiopathology*; D016649:Primary Ovarian Insufficiency / Q000175:diagnosis* / Q000378:metabolism / Q000503:physiopathology; D012720:Severity of Illness Index
chemical_list: D015415:Biomarkers